class_docstr: A MLP block that contains two linear layers with a normalization layer. The MLP
  block is used in a transformer model after the attention block.
  
  ::
  
                       Linear (in_features, hidden_features)
                                         ↓
                               Normalization (act_layer)
                                         ↓
                              Dropout (p=dropout_rate)
                                         ↓
                       Linear (hidden_features, out_features)
                                         ↓
                              Dropout (p=dropout_rate)
docstr: Args:
      x (tensor): Input tensor.
docstr_tok: ["Args",":","x","(","tensor",")",":","Input","tensor","."]
code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      """
      Args:
          x (tensor): Input tensor.
      """
      x = self.fc1(x)
      x = self.act(x)
      x = self.fc2(x)
      return x
  
imports: from typing import List, Optional, Tuple
  import numpy
  import torch
  import torch.fx
  import torch.nn
  from torch.nn.common_types import _size_3_t
  from .drop_path import DropPath
label_desc: Use image node_id 2 for calling the Mlp obj's underlying member method code with example usage: obj.forward(x) and returns: x